Evaluation of selected Climate Extreme Indices (CEIs) from BC climate extremes app

Author
Affiliation

Aseem Sharma e-mail: aseem.sharma@gov.bc.ca

Future Forest Ecosystems Centre, FCCSB, OCF, BC Ministry of Forests

Published

July 17, 2025

1 Background

This document presents an evaluation of selected Climate Extremes Indices (CEIs) generated and visualized in the bc_climate_extremes_app (referred to as CEIapp hereafter). The primary objectives are twofold:

  1. To clarify the calculation methods for specific CEIs whose definitions or computational procedures are not sufficiently detailed in their definition and description Appendix 1
  2. To assess the consistency and performance of CEIs produced by the app in comparison with similar indices from established sources or input data.

The CEIapp provides a suite of over 70 CEIs, derived from the Multi-Source Weather (MSWX) gridded dataset (Beck et al., 2022), which includes daily minimum and maximum temperatures and precipitation across western North America. Several CEIs also incorporate spatial coordinates (latitude and longitude) and the month of the year in their calculations to account for spatial and seasonal variability. This dataset has a spatial resolution of 0.1° × 0.1° and spans the period from 1979 to present. For the current analysis, we limit the temporal extent to 2024, the most recent year for which complete data were available. The app will be updated periodically to incorporate indices for subsequent years.

Although the app includes over 70 CEIs (listed in Appendix 1), the scope of this evaluation is limited to a subset of sector-relevant indices, as many of the indices are already well-defined and sufficiently described. Selected indices evaluated here include the drought index SPEI, the heatwave-related indices, and the precipitation-related indices.

2 Standardized Precipitation-Evapotranspiration Index (SPEI)

We calculated the Standardized Precipitation-Evapotranspiration Index (SPEI) drought index using the climpact R package , which internally uses the SPEI R package to compute SPEI values. The SPEI is calculated as the climatic water balance obtained at various time scales (here: 3-month, 6-month, and 12-month) as shown in equation (i) (Vicente-Serrano et al., 2010):

\[ D_i = P_i - PET_i \tag{i} \]

where:
\(P_i\) is the accumulated precipitation for period i,
\(PET_i\) is the potential evapotranspiration, and
\(D_i\) is the climate water balance.

The time series of \(D_i\) values is then standardized (mean 0, standard deviation 1) using a log-logistic distribution to produce unitless SPEI values (Vicente-Serrano et al., 2010). These standardized values account for seasonal and regional variability, enabling comparison across time and space.

There are various methods to calculate PET, such as Thornthwaite, Penman-Monteith, and Hargreaves. In the CEIapp, the \(PET ( ET_0 )\) is calculated using a modified Hargreaves method, an empirical approach that requires limited input data and relies primarily on temperature and extraterrestrial radiation (Ra), which can be calculated from latitude and Julian day as in equation (ii).

\[ ET_o = 0.0023 \times Ra \times (T_{avg} + 17.8) \times (T_{max} - T_{min})^{0.5} \tag{ii} \]

where:
\(ET_0\) = evapotranspiration,
\(Ra\) = extraterrestrial radiation,
\(T_{avg}\), \(T_{max}\), \(T_{min}\) = average, maximum, and minimum daily temperatures.

The calculated SPEI can be used to indicate the severity of drought with negative and positive SPEI indicating dry and wet conditions as in Table 1:

SPEI Value Drought Condition
≤ -2.00 Extremely Dry
-1.50 to -1.99 Severely Dry
-1.00 to -1.49 Moderately Dry
-0.99 to 0.99 Normal
1.00 to 1.49 Moderately Wet
1.50 to 1.99 Very Wet
≥ 2.00 Extremely Wet
Table 1: Categories of drought condition based on SPEI values.

We compared our SPEI values with those from the global SPEI database, which provides long-term SPEI data (1950–2025) at 1° × 1° spatial resolution using the CRU TS 4.09 dataset (Harris et al. (2020)). This database provides SPEI for accumulation periods ranging from 1 to 48 months. For our comparison, we focused on 3-, 6-, and 12-month periods using a BC subset of the global dataset.

Figure 1 shows a spatial comparison of SPEI across BC at three temporal scales—3, 6, and 12 months— for July 2023, one of the highest drought months. The figure indicates detailed drought conditions as shown by SPEI with the higher resolution outputs of the CEIapp (left panel) than the coarser-resolution global SPEI ( right panel). Although the pattern of SPEI is captured well across BC especially for 3-months period, it differs substantially for 6 and 12 months especially along the Coast Mountains region of BC. Furthermore, the SPEI calculated for CEIapp consistently indicates widespread drought conditions across BC for all three accumulation periods (3, 6, and 12 months). Drought severity intensifies with increasing accumulation periods, a pattern particularly evident in the 12-month SPEI map (Figure 1 a), which depicts pervasive drought throughout the province. In contrast, the global SPEI dataset exhibits greater spatial variability, with certain regions not indicating drought. While the SPEI from CEIapp suggests a more uniform and widespread drought pattern, the global SPEI database illustrates localized areas—particularly along the western coast—where drought conditions are less pronounced or absent in the global SPEI data. Given the inherently regional nature of drought, the extreme app’s SPEI appears to provide a more consistent and regionally appropriate representation of drought conditions in BC compared to the global dataset.

Figure 1: Spatial pattern of 3, 6 and 12-month SPEI calculated from (a.) MSWX based CEI database from the bc_climate_extremes_app and (b.) using global drought monitor database for July 2023.

We also calculated correlation and other comparison metrics—including Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Integrated Quadratic Distance (IQD) which quantifies the difference between two distribution functions by integrating the squared differences across their range (Thorarinsdottir et al. (2013)) —between the extreme app’s SPEI and the global SPEI datasets. These metrics assess the degree of agreement and error between the SPEIs from the CEIapp and global SPEI database.

The 3-month accumulation of the SPEI shows higher correlation and lower RMSE and IQD between the extreme app and global SPEI datasets (Figure 2). This indicates relatively strong agreement at shorter accumulation timescales. However, as the accumulation period increases (e.g., to 6 or 12 months), the correlation weakens and error metrics increase, suggesting greater discrepancies between the datasets. This divergence i.e, the reduced comparability of SPEI values at longer accumulation periods, is likely attributable to differences in dataset resolution and quality (MSWX (0.1°) Beck et al. (2022) versus CRU TS (1°) Harris et al. (2020)) and methodological variations in PET estimation (CEIapp uses Hargreaves; global datasets may use Thornthwaite or Penman-Monteith) .

Figure 2: Spatial comparison coefficients between CEIapp SPEI and global SPEI database over the period of 1979 to 2025 for 3- 6- and 12- months.

3 Heatwave and temperature indices

We calculated the heatwave number, frequency and duration using the climpact R package and the heatwave aspects are defined based on minimum and maximum temperature thresholds and the Excess Heat Factor (EHF). The maximum (minimum) temperature heatwaves are defined as any period of three or more days when daily maximum (minimum) temperature ((TX)(TN)) exceeds the 90th percentile for the corresponding calendar day. EHF heatwaves are defined as any period of three or more days when the EHF is positive. The EHF is calculated as in equation (iii) where \(EHI_{sig}\) and \(EHI_{acc}\) are two excess heat indices (EHI) representing the potential to acclimatize to and the climatological significance of the heat on a particular day and calculated as in equations (iv) and (v) following Nairn & Fawcett (2013).

\[ EHF = EHI_{sig} \times EHI_{acc} \tag{iii} \]

\[ EHI_{sig} = (T_{i} + T_{i-1} + T_{i-2})/3 - T_{95} \tag{iv} \] \[ EHI_{acc} = (T_{i} + T_{i-1} + T_{i-2})/3 - (T_{i-1} + ...+ T_{i-30})/30 \tag{v} \]

where \(T_i\) is the daily temperature for day \(i\) and \(T_{95}\) is the 95th percentile of \(T_i\) over all days within the specified base period i.e., 1981-2010. Since heatwave indices are directly derived from daily minimum and maximum temperatures, we first evaluate the MSWX daily temperature data against observed station data across BC. This comparison serves to assess the representativeness of the MSWX dataset, and the reliability of the heatwave indices computed in the CEIapp. We focus on two key comparisons: (1) the 2021 heatwave event, one of the most significant in BC’s recent history and (2) a long-term evaluation across three stations located at different elevations and different parts of BC. These analyses provide insights into how accurately MSWX data captures daily temperature, and, by extension, the robustness of heatwave-related indices presented in the CEIapp.

3.1 Heatwave 2021

Figure 3: Comparison of daily minimum and maximum temperatures from the MSWX gridded dataset and observed station data across BC, averaged over the 2021 heatwave period i.e., June 25 to July 2, 2021.
Figure 4: Same as Figure 3 but focused on the lower-latitude region of BC that experienced the most severe impacts of the 2021 heatwave. This zoomed-in view allows for a more detailed comparison of daily minimum and maximum temperatures from MSWX and station observations and shows how well MSWX daily data captures localized heatwave.

Figure 3 (for all of BC) and Figure 4 (focused on lower-latitude regions of BC) provide a visual comparison of how daily minimum and maximum temperatures were captured by the MSWX daily temperature data relative to observed station data during the peak of the June 2021 heatwave (June 25 to July 2, 2021). Overall, the MSWX data shows strong agreement with observations, with an average difference of only 0.2°C for maximum temperatures and –1.5°C for minimum temperatures across all stations.

3.2 Long-term daily temperature evaluation

Figure 5: Location of three selected stations with different elevations and long-term daily data availability for comparative analysis.
Station ID MAE RMSE Bias Corr (r) IQD
1095018 Tmin 2.47 3.49 -0.75 0.92 0.03
Tmax 2.25 3.21 0.05 0.95 0.01
1103332 Tmin 1.37 1.87 0.17 0.95 0.05
Tmax 1.72 2.30 -0.03 0.96 0.01
EAC Tmin 2.51 3.20 -0.27 0.93 0.06
Tmax 2.78 3.50 0.40 0.95 0.07
Average Tmin 2.12 2.85 -0.28 0.93 0.05
Tmax 2.25 3.00 0.14 0.95 0.03
Table 2: Comparison coefficients between observed and MSWX data for the period of 1980 to 2024 across selected three stations in BC.

A long-term comparison of daily MSWX and observed temperature from three selected stations in BC spanning a range of elevations (Figure 5) over the period 1980 to 2024 demonstrates good agreement between these two datasets (Table 2 and Figure 6). Correlation coefficients (r) are consistently strong for both Tmin (0.93) and Tmax (0.95) on average. Average MAE values are 2.12 for Tmin and 2.25 for Tmax, indicating good accuracy. While minor biases exist, the overall consistency and low IQD values suggest the MSWX daily temperature is reliable for heatwave indices.

Figure 6: One on one plot of daily temperature between MSWX and observation for selected 3 stations covering different elevations across BC.

The 1:1 scatter plot of both minimum (Tmin) and maximum (Tmax) temperatures shows that the MSWX temperatures closely align with observation, as indicated by the tight clustering of points around the 1:1 line (Figure 6). This strong linear agreement suggests that MSWX effectively captures daily temperature variability and extremes across different elevations and regions. Despite minor discrepancies, especially at lower temperatures for station 1095018, the overall consistency underscores the reliability of MSWX for representing historical daily temperature and their extremes.

These results, based on both the detailed comparison of the 2021 heatwave and the long-term evaluation, indicate that the MSWX dataset reliably represents extreme temperature conditions. Consequently, the heatwave indices derived from the CEI app can be considered a reliable representation of heatwave conditions in BC.

4 Precipitation and precipitation indices

Further, we compared daily precipitation and precipitation-related climate extreme indices—R20mm (days with precipitation ≥ 20 mm) and PRCPTOT (annual total precipitation). The MSWX gridded data generally aligns with the observed station data in terms of the timing and frequency of daily precipitation events aligning visually with observed wet and dry periods (Figure 7) however there is consistent underestimation of observed high magnitude precipitation events (Figure 8). Moreover, there is generally poor correlation and negative bias on daily precipitation for higher elevation stations (Table 3).

Figure 7: Temporal evolution and comparison of daily total precipitation from station observations and corresponding values extracted from the MSWX gridded dataset at station locations.
Figure 8: One-to-one plot comparing observed station daily precipitation with corresponding values extracted from the MSWX gridded dataset.
Station ID MAE RMSE Bias Corr (r) IQD
1095018 1.730 3.470 -0.010 0.370 0.016
1103332 5.73 10.62 0.02 0.48 0.02
EAC 3.00 5.72 -0.14 0.56 0.04
Table 3: Comparison coefficients between observed and MSWX daily precipitation data from 1980 to 2024 at three selected stations in BC.

Moreover, a one-to-one comparison of observed station data and MSWX-derived values for two precipitation-related climate indices—R20mm (number of days with precipitation ≥ 20 mm) and PRCPTOT (annual total wet-day precipitation)—shows that MSWX generally agrees with station-based indices at lower elevation sites (Figure 9). However, at the higher elevation station (e.g., EAC), and particularly for higher-magnitude precipitation values, MSWX tends to underestimate both total precipitation and R20mm reinforcing what was observed in the comparison of the daily precipitation data highlighting MSWX’s limitations in accurately capturing extreme precipitation indices, especially in complex topographic regions.

Figure 9: One-to-one plots comparing R20mm and annual total precipitation (PRCPTOT) between observed data and MSWX-derived values for three selected stations.

5 Summary

This report provides a preliminary assessment of how well CEIs derived from the MSWX dataset represent climate extremes in BC and offers guidance to users on how to interpret and apply results from the CEIapp. Based on the analysis of SPEI, heatwave events, and precipitation-related indices, the following conclusions can be drawn:

  • SPEI Performance: Although the 3-month SPEI values are comparable between the CEIapp and global SPEI database, the CEIapp-based SPEI shows greater spatial detail and better alignment with regional drought patterns. It also performs more consistently across longer accumulation periods (6- and 12-month), making it a more accurate representation of drought conditions in BC compared to the global SPEI datasets.

  • Heatwave and temperature extremes: The MSWX daily temperature data effectively captures the extreme 2021 heatwave, with only a 0.5°C difference in mean maximum temperatures compared to observed station data. Long-term temperature also shows good agreement, indicating that MSWX reliably represents heatwave and temperature-related extremes conditions across the province.

  • Precipitation Indices: While MSWX captures the temporal evolution of daily precipitation fairly well at lower magnitudes, it tends to underestimate high-magnitude precipitation events, especially in higher elevations. As a result, precipitation-related CEIs derived from MSWX are only moderately representative and should be used with caution, particularly when analyzing extremes or localized heavy precipitation events.

This evaluation and comparison of CEIs and the input data used to calculate them in the CEIapp offer an initial level of confidence and insight into the (un)certainty of how well MSWX-based CEIs are represented. It aims to give users information on how they might want to approach the data and results from the CEIapp. However, it is important to note that this evaluation is based on a limited number of selected stations and may not fully represent the broader spatial performance across BC. A more comprehensive assessment across additional stations and regions is beyond the scope of this work. Users should use this as a guidance and exercise their own discretion when interpreting and utilizing the data and results provided by the CEIapp.

6 References

Beck, H. E., Van Dijk, A. I. J. M., Larraondo, P. R., McVicar, T. R., Pan, M., Dutra, E., & Miralles, D. G. (2022). Global 3-Hourly 0.1 Bias-Corrected Meteorological Data Including Near-Real-Time Updates and Forecast Ensembles. Bulletin of the American Meteorological Society, 103(3), E710–E732. https://doi.org/10.1175/BAMS-D-21-0145.1
Harris, I., Osborn, T. J., Jones, P., & Lister, D. (2020). Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Scientific Data, 7(1), 1–18. https://doi.org/10.1038/s41597-020-0453-3
Nairn, J. R., & Fawcett, Robert. (2013). Defining heatwaves : heatwave defined as a heat-impact event servicing all community and business sectors in Australia (p. 84). CAWCR Technical Report No. 060; Centre for Australian Weather; Climate Research.
Thorarinsdottir, T. L., Gneiting, T., & Gissibl, N. (2013). Using proper divergence functions to evaluate climate models. SIAM-ASA Journal on Uncertainty Quantification, 1(1), 522–534. https://doi.org/10.1137/130907550
Vicente-Serrano, S. M., Beguería, S., & López-Moreno, J. I. (2010). A multiscalar drought index sensitive to global warming: The standardized precipitation evapotranspiration index. Journal of Climate, 23(7), 1696–1718. https://doi.org/10.1175/2009JCLI2909.1

7 Appendix

Appendix 1: List of the CEIs with their definition, units and descriptions

Modified from Climpact R package user guide.

Index Index _name Units Definition Description Timescale
CDD (cdd) Consecutive Dry Days days Maximum number of consecutive dry days (when PR < 1) Longest dry spell Ann
CDDcoldn (cddcold18) Cooling Degree Days degree-days Annual sum of TM - n (where n , n = 18) A measure of the energy demand needed to cool a building Ann
CSDI (csdi) Cold spell duration indicator days Annual number of days contributing to events where 6 or more consecutive days experience TN < 10th percentile Number of days contributing to a cold period (where the period has to be at least 6 days long) Ann
CSDId (csdi5) User-defined CSDI days Annual number of days contributing to events where d or more consecutive days experience TN < 10th percentile Number of days contributing to a cold period (where the minimum length is 5) Ann
CWD (cwd) Consecutive Wet Days days Maximum annual number of consecutive wet days (when PR >= 1) The longest wet spell Ann
DTR (dtr) Daily Temperature Range degrees_C Mean difference between daily TX and daily TN Average range of maximum and minimum temperature Mon/Ann
DTR (dtr) Daily Temperature Range degrees_C Mean difference between daily TX and daily TN Average range of maximum and minimum temperature Mon/Ann
FD (fd) Frost Days days Number of days when TN < 0 C Days when minimum temperature is below 0C Mon/Ann
FD (fd) Frost Days days Number of days when TN < 0 C Days when minimum temperature is below 0C Mon/Ann
GDDgrown (gddgrow10) Growing Degree Days degree-days Annual sum of TM - n (where n is a user-defined location-specific base temperature and TM > n) A measure of heat accumulation to predict plant and animal developmental rates Ann
GSL (gsl) Growing Season Length days Annual length of days plant can growth Length of time in which plants can grow (Annual number of days between the first occurrence of 6 consecutive days with TM > 5 degrees_C and the first occurrence of 6 consecutive days with TM < 5 C) Ann
HDDheatn (hddheat18) Heating Degree Days degree-days Annual sum of n - TM (where n is a user-defined location-specific base temperature and TM < n) A measure of the energy demand needed to heat a building Ann
HW (hw) Heatwave magnitude for Tx90 heatwaves degC Heatwave and Coldwave duration (HWD), magnitude (HWD), Frequency (HWF) based on tempearture. Annual Heat wave and Cold wave magnitude amplitude number duration and frequency calculated from TX and TN Ann
HW (hw) Heatwave magnitude for Tn90 heatwaves degC Heatwave and Coldwave duration (HWD), magnitude (HWD), Frequency (HWF) based on tempearture. Annual Heat wave and Cold wave magnitude amplitude number duration and frequency calculated from TX and TN Ann
HW (hw) Heatwave magnitude for EHF heatwaves degC^2 Heatwave and Coldwave duration (HWD), magnitude (HWD), Frequency (HWF) based on tempearture. Annual Heat wave and Cold wave magnitude amplitude number duration and frequency calculated from TX and TN Ann
HW (hw) Coldwave magnitude for ECF coldwaves degC^2 Heatwave and Coldwave duration (HWD), magnitude (HWD), Frequency (HWF) based on tempearture. Annual Heat wave and Cold wave magnitude amplitude number duration and frequency calculated from TX and TN Ann
HW (hw) Heatwave amplitude for Tx90 heatwaves degC Heatwave and Coldwave duration (HWD), magnitude (HWD), Frequency (HWF) based on tempearture. Annual Heat wave and Cold wave magnitude amplitude number duration and frequency calculated from TX and TN Ann
HW (hw) Heatwave amplitude for Tn90 heatwaves degC Heatwave and Coldwave duration (HWD), magnitude (HWD), Frequency (HWF) based on tempearture. Annual Heat wave and Cold wave magnitude amplitude number duration and frequency calculated from TX and TN Ann
HW (hw) Heatwave amplitude for EHF heatwaves degC^2 Heatwave and Coldwave duration (HWD), magnitude (HWD), Frequency (HWF) based on tempearture. Annual Heat wave and Cold wave magnitude amplitude number duration and frequency calculated from TX and TN Ann
HW (hw) Coldwave amplitude for ECF coldwaves degC^2 Heatwave and Coldwave duration (HWD), magnitude (HWD), Frequency (HWF) based on tempearture. Annual Heat wave and Cold wave magnitude amplitude number duration and frequency calculated from TX and TN Ann
HW (hw) Heatwave number for Tx90 heatwaves heatwaves Heatwave and Coldwave duration (HWD), magnitude (HWD), Frequency (HWF) based on tempearture. Annual Heat wave and Cold wave magnitude amplitude number duration and frequency calculated from TX and TN Ann
HW (hw) Heatwave number for Tn90 heatwaves heatwaves Heatwave and Coldwave duration (HWD), magnitude (HWD), Frequency (HWF) based on tempearture. Annual Heat wave and Cold wave magnitude amplitude number duration and frequency calculated from TX and TN Ann
HW (hw) Heatwave number for EHF heatwaves heatwaves Heatwave and Coldwave duration (HWD), magnitude (HWD), Frequency (HWF) based on tempearture. Annual Heat wave and Cold wave magnitude amplitude number duration and frequency calculated from TX and TN Ann
HW (hw) Coldwave number for ECF coldwaves heatwaves Heatwave and Coldwave duration (HWD), magnitude (HWD), Frequency (HWF) based on tempearture. Annual Heat wave and Cold wave magnitude amplitude number duration and frequency calculated from TX and TN Ann
HW (hw) Heatwave duration for Tx90 heatwaves days Heatwave and Coldwave duration (HWD), magnitude (HWD), Frequency (HWF) based on tempearture. Annual Heat wave and Cold wave magnitude amplitude number duration and frequency calculated from TX and TN Ann
HW (hw) Heatwave duration for Tn90 heatwaves days Heatwave and Coldwave duration (HWD), magnitude (HWD), Frequency (HWF) based on tempearture. Annual Heat wave and Cold wave magnitude amplitude number duration and frequency calculated from TX and TN Ann
HW (hw) Heatwave duration for EHF heatwaves days Heatwave and Coldwave duration (HWD), magnitude (HWD), Frequency (HWF) based on tempearture. Annual Heat wave and Cold wave magnitude amplitude number duration and frequency calculated from TX and TN Ann
HW (hw) Coldwave duration for ECF coldwaves days Heatwave and Coldwave duration (HWD), magnitude (HWD), Frequency (HWF) based on tempearture. Annual Heat wave and Cold wave magnitude amplitude number duration and frequency calculated from TX and TN Ann
HW (hw) Heatwave frequency for Tx90 heatwaves days Heatwave and Coldwave duration (HWD), magnitude (HWD), Frequency (HWF) based on tempearture. Annual Heat wave and Cold wave magnitude amplitude number duration and frequency calculated from TX and TN Ann
HW (hw) Heatwave frequency for Tn90 heatwaves days Heatwave and Coldwave duration (HWD), magnitude (HWD), Frequency (HWF) based on tempearture. Annual Heat wave and Cold wave magnitude amplitude number duration and frequency calculated from TX and TN Ann
HW (hw) Heatwave frequency for EHF heatwaves days Heatwave and Coldwave duration (HWD), magnitude (HWD), Frequency (HWF) based on tempearture. Annual Heat wave and Cold wave magnitude amplitude number duration and frequency calculated from TX and TN Ann
HW (hw) Coldwave frequency for ECF coldwaves days Heatwave and Coldwave duration (HWD), magnitude (HWD), Frequency (HWF) based on tempearture. Annual Heat wave and Cold wave magnitude amplitude number duration and frequency calculated from TX and TN Ann
ID (id) Ice Days days Number of days when TX < 0 C Days when maximum temperature is below 0C Mon/Ann
ID (id) Ice Days days Number of days when TX < 0 C Days when maximum temperature is below 0C Mon/Ann
PRCPTOT (prcptot) Annual total wet-day precipitation mm Sum of daily PR >= 1 Total wet-day rainfall Mon/Ann
PRCPTOT (prcptot) Annual total wet-day precipitation mm Sum of daily PR >= 1 Total wet-day rainfall Mon/Ann
R10mm (r10mm) Number of heavy rain days days Number of days when PR >= 10 mm Days when rainfall is at least 10mm Mon/Ann
R10mm (r10mm) Number of heavy rain days days Number of days when PR >= 10 mm Days when rainfall is at least 10mm Mon/Ann
R20mm (r20mm) Number of very heavy rain days days Number of days when PR >= 20 mm Days when rainfall is at least 20mm Mon/Ann
R20mm (r20mm) Number of very heavy rain days days Number of days when PR >= 20 mm Days when rainfall is at least 20mm Mon/Ann
Rnnmm (r30mm) Number of customized rain days days Number of days when PR >= nn Days when rainfall is at least a user-specified number of mm Mon/Ann
Rnnmm (r30mm) Number of customized rain days days Number of days when PR >= nn Days when rainfall is at least a user-specified number of mm Mon/Ann
R95p (r95p) Total annual precipitation from heavy rain days mm Annual sum of daily PR > 95th percentile Amount of rainfall from very wet days Ann
R95pTOT (r95ptot) Contribution from very wet days % 100*r95p / PRCPTOT Fraction of total wet-day rainfall that comes from very wet days Ann
R99p (r99p) Total annual precipitation from very heavy rain days mm Annual sum of daily PR > 99th percentile Amount of rainfall from extremely wet days Ann
R99pTOT (r99ptot) Contribution from extremely wet days % 100*r99p / PRCPTOT Fraction of total wet-day rainfall that comes from extremely wet days Ann
Rx1day (rx1day) Max 1-day precipitation mm Maximum 1-day PR total Maximum amount of rain that falls in one day Mon/Ann
Rx1day (rx1day) Max 1-day precipitation calendar day Maximum 1-day PR total Maximum amount of rain that falls in one day Mon/Ann
Rx1day (rx1day) Max 1-day precipitation mm Maximum 1-day PR total Maximum amount of rain that falls in one day Mon/Ann
Rx1day (rx1day) Max 1-day precipitation calendar day Maximum 1-day PR total Maximum amount of rain that falls in one day Mon/Ann
Rx5day (rx5day) Max 5-day precipitation mm Maximum 5-day PR total Maximum amount of rain that falls in five consecutive days Mon/Ann
Rx5day (rx5day) Max 5-day precipitation calendar day Maximum 5-day PR total Maximum amount of rain that falls in five consecutive days Mon/Ann
Rx5day (rx5day) Max 5-day precipitation mm Maximum 5-day PR total Maximum amount of rain that falls in five consecutive days Mon/Ann
Rx5day (rx5day) Max 5-day precipitation calendar day Maximum 5-day PR total Maximum amount of rain that falls in five consecutive days Mon/Ann
RXdday (rx7day) User-defined consecutive days PR amount mm Maximum d-day PR total Maximum amount of rain that falls in a user-specified period i Mon/Ann
RXdday (rx7day) User-defined consecutive days PR amount calendar day Maximum d-day PR total Maximum amount of rain that falls in a user-specified period i Mon/Ann
RXdday (rx7day) User-defined consecutive days PR amount mm Maximum d-day PR total Maximum amount of rain that falls in a user-specified period i Mon/Ann
RXdday (rx7day) User-defined consecutive days PR amount calendar day Maximum d-day PR total Maximum amount of rain that falls in a user-specified period i Mon/Ann
SDII (sdii) Daily precipitation intensity mm/day Annual total PR divided by the number of wet days (when total PR >= 1) Average daily wet-day rainfall intensity Ann
SPEI (spei) Standardised Precipitation Evapotranspiration Index unitless Standardised Precipitation Evapotranspiration Index Measure of ‘drought’ using the Standardised Precipitation Evapotranspiration Index on time scales of 3 months 6 months and 12 months Mon
SPEI (spei) Standardised Precipitation Evapotranspiration Index unitless Standardised Precipitation Evapotranspiration Index Measure of ‘drought’ using the Standardised Precipitation Evapotranspiration Index on time scales of 3 months 6 months and 12 months Mon
SPEI (spei) Standardised Precipitation Evapotranspiration Index unitless Standardised Precipitation Evapotranspiration Index Measure of ‘drought’ using the Standardised Precipitation Evapotranspiration Index on time scales of 3 months 6 months and 12 months Mon
SPI (spi) Standardised Precipitation Index unitless Standardised Precipitation Index Measure of ‘drought’ using the Standardised Precipitation Index on time scales of 3 months 6 months and 12 months Mon
SPI (spi) Standardised Precipitation Index unitless Standardised Precipitation Index Measure of ‘drought’ using the Standardised Precipitation Index on time scales of 3 months 6 months and 12 months Mon
SPI (spi) Standardised Precipitation Index unitless Standardised Precipitation Index Measure of ‘drought’ using the Standardised Precipitation Index on time scales of 3 months 6 months and 12 months Mon
SU (su) Summer days days Number of days when TX > 25 C Days when maximum temperature exceeds 25C Mon/Ann
SU (su) Summer days days Number of days when TX > 25 C Days when maximum temperature exceeds 25C Mon/Ann
TMge10 (tmge10) Mean temperature of at least 10C days Number of days when TM >= 10 C Days when average temperature is at least 10C Mon/Ann
TMge10 (tmge10) Mean temperature of at least 10C days Number of days when TM >= 10 C Days when average temperature is at least 10C Mon/Ann
TMge5 (tmge5) Mean temperature of at least 5C days Number of days when TM >= 5 C Days when average temperature is at least 5C Mon/Ann
TMge5 (tmge5) Mean temperature of at least 5C days Number of days when TM >= 5 C Days when average temperature is at least 5C Mon/Ann
TMlt10 (tmlt10) Mean temperature below 10C days Number of days when TM < 10 C Days when average temperature is below 10C Mon/Ann
TMlt10 (tmlt10) Mean temperature below 10C days Number of days when TM < 10 C Days when average temperature is below 10C Mon/Ann
TMlt5 (tmlt5) Mean temperature below 5C days Number of days when TM < 5 C Days when average temperature is below 5C Mon/Ann
TMlt5 (tmlt5) Mean temperature below 5C days Number of days when TM < 5 C Days when average temperature is below 5C Mon/Ann
TMm (tmm) Mean daily mean temperature degrees_C Mean daily mean temperature Average daily temperature Mon/Ann
TMm (tmm) Mean daily mean temperature degrees_C Mean daily mean temperature Average daily temperature Mon/Ann
TN10p (tn10p) Amount of cold nights % Percentage of days when TN < 10th percentile Fraction of days with cold night time temperatures Ann
TN10p (tn10p) Amount of cold nights % Percentage of days when TN < 10th percentile Fraction of days with cold night time temperatures Ann
TN90p (tn90p) Amount of warm nights % Percentage of days when TN > 90th percentile Fraction of days with warm night time temperatures Ann
TN90p (tn90p) Amount of warm nights % Percentage of days when TN > 90th percentile Fraction of days with warm night time temperatures Ann
TNlt2 (tnlt2) Minimum temperature below 2C days Number of days when TN < 2 C Days when minimum temperature is below 2C Mon/Ann
TNlt2 (tnlt2) Minimum temperature below 2C days Number of days when TN < 2 C Days when minimum temperature is below 2C Mon/Ann
TNltm2 (tnltm2) Minimum temperature below -2C days Number of days when TN < -2 C Days when minimum temperature is below -2C Mon/Ann
TNltm2 (tnltm2) Minimum temperature below -2C days Number of days when TN < -2 C Days when minimum temperature is below -2C Mon/Ann
TNltm20 (tnltm20) Minimum temperature below -20C days Num